kube-bench/docs/running.md

Running kube-bench

If you run kube-bench directly from the command line you may need to be root / sudo to have access to all the config files.

By default kube-bench attempts to auto-detect the running version of Kubernetes, and map this to the corresponding CIS Benchmark version. For example, Kubernetes version 1.15 is mapped to CIS Benchmark version cis-1.15 which is the benchmark version valid for Kubernetes 1.15.

kube-bench also attempts to identify the components running on the node, and uses this to determine which tests to run (for example, only running the master node tests if the node is running an API server).

Please note It is impossible to inspect the master nodes of managed clusters, e.g. GKE, EKS, AKS and ACK, using kube-bench as one does not have access to such nodes, although it is still possible to use kube-bench to check worker node configuration in these environments.

Running inside a container

You can avoid installing kube-bench on the host by running it inside a container using the host PID namespace and mounting the /etc and /var directories where the configuration and other files are located on the host so that kube-bench can check their existence and permissions.

docker run --pid=host -v /etc:/etc:ro -v /var:/var:ro -t docker.io/aquasec/kube-bench:latest --version 1.18

Note: the tests require either the kubelet or kubectl binary in the path in order to auto-detect the Kubernetes version. You can pass -v $(which kubectl):/usr/local/mount-from-host/bin/kubectl to resolve this. You will also need to pass in kubeconfig credentials. For example:

docker run --pid=host -v /etc:/etc:ro -v /var:/var:ro -v $(which kubectl):/usr/local/mount-from-host/bin/kubectl -v ~/.kube:/.kube -e KUBECONFIG=/.kube/config -t docker.io/aquasec/kube-bench:latest 

You can use your own configs by mounting them over the default ones in /opt/kube-bench/cfg/

docker run --pid=host -v /etc:/etc:ro -v /var:/var:ro -t -v path/to/my-config.yaml:/opt/kube-bench/cfg/config.yaml -v $(which kubectl):/usr/local/mount-from-host/bin/kubectl -v ~/.kube:/.kube -e KUBECONFIG=/.kube/config docker.io/aquasec/kube-bench:latest

Running in a Kubernetes cluster

You can run kube-bench inside a pod, but it will need access to the host's PID namespace in order to check the running processes, as well as access to some directories on the host where config files and other files are stored.

The job.yaml file (available in the root directory of the repository) can be applied to run the tests as a Kubernetes Job. For example:

$ kubectl apply -f job.yaml
job.batch/kube-bench created

$ kubectl get pods
NAME                      READY   STATUS              RESTARTS   AGE
kube-bench-j76s9   0/1     ContainerCreating   0          3s

# Wait for a few seconds for the job to complete
$ kubectl get pods
NAME                      READY   STATUS      RESTARTS   AGE
kube-bench-j76s9   0/1     Completed   0          11s

# The results are held in the pod's logs
kubectl logs kube-bench-j76s9
[INFO] 1 Master Node Security Configuration
[INFO] 1.1 API Server
...

To run tests on the master node, the pod needs to be scheduled on that node. This involves setting a nodeSelector and tolerations in the pod spec.

The default labels applied to master nodes has changed since Kubernetes 1.11, so if you are using an older version you may need to modify the nodeSelector and tolerations to run the job on the master node.

Running in an AKS cluster

1. Create an AKS cluster(e.g. 1.13.7) with RBAC enabled, otherwise there would be 4 failures

2. Use the kubectl-enter plugin to shell into a node kubectl-enter {node-name} or ssh to one agent node could open nsg 22 port and assign a public ip for one agent node (only for testing purpose)

3. Run CIS benchmark to view results:

docker run --rm -v `pwd`:/host docker.io/aquasec/kube-bench:latest install
./kube-bench 

kube-bench cannot be run on AKS master nodes

Running CIS benchmark in an EKS cluster

There is a job-eks.yaml file for running the kube-bench node checks on an EKS cluster. The significant difference on EKS is that it's not possible to schedule jobs onto the master node, so master checks can't be performed

1. To create an EKS Cluster refer to Getting Started with Amazon EKS in the Amazon EKS User Guide

• Information on configuring eksctl, kubectl and the AWS CLI is within

2. Create an Amazon Elastic Container Registry (ECR) repository to host the kube-bench container image

aws ecr create-repository --repository-name k8s/kube-bench --image-tag-mutability MUTABLE

3. Download, build and push the kube-bench container image to your ECR repo

git clone https://github.com/aquasecurity/kube-bench.git
cd kube-bench
aws ecr get-login-password --region <AWS_REGION> | docker login --username AWS --password-stdin <AWS_ACCT_NUMBER>.dkr.ecr.<AWS_REGION>.amazonaws.com
docker build -t k8s/kube-bench .
docker tag k8s/kube-bench:latest <AWS_ACCT_NUMBER>.dkr.ecr.<AWS_REGION>.amazonaws.com/k8s/kube-bench:latest
docker push <AWS_ACCT_NUMBER>.dkr.ecr.<AWS_REGION>.amazonaws.com/k8s/kube-bench:latest

4. Copy the URI of your pushed image, the URI format is like this: <AWS_ACCT_NUMBER>.dkr.ecr.<AWS_REGION>.amazonaws.com/k8s/kube-bench:latest
5. Replace the image value in job-eks.yaml with the URI from Step 4
6. Run the kube-bench job on a Pod in your Cluster: kubectl apply -f job-eks.yaml
7. Find the Pod that was created, it should be in the default namespace: kubectl get pods --all-namespaces
8. Retrieve the value of this Pod and output the report, note the Pod name will vary: kubectl logs kube-bench-<value>

• You can save the report for later reference: kubectl logs kube-bench-<value> > kube-bench-report.txt

Running DISA STIG in an EKS cluster

There is a job-eks-stig.yaml file for running the kube-bench node checks on an EKS cluster. The significant difference on EKS is that it's not possible to schedule jobs onto the master node, so master checks can't be performed

1. To create an EKS Cluster refer to Getting Started with Amazon EKS in the Amazon EKS User Guide

• Information on configuring eksctl, kubectl and the AWS CLI is within

2. Create an Amazon Elastic Container Registry (ECR) repository to host the kube-bench container image

aws ecr create-repository --repository-name k8s/kube-bench --image-tag-mutability MUTABLE

3. Download, build and push the kube-bench container image to your ECR repo

git clone https://github.com/aquasecurity/kube-bench.git
cd kube-bench
aws ecr get-login-password --region <AWS_REGION> | docker login --username AWS --password-stdin <AWS_ACCT_NUMBER>.dkr.ecr.<AWS_REGION>.amazonaws.com
docker build -t k8s/kube-bench .
docker tag k8s/kube-bench:latest <AWS_ACCT_NUMBER>.dkr.ecr.<AWS_REGION>.amazonaws.com/k8s/kube-bench:latest
docker push <AWS_ACCT_NUMBER>.dkr.ecr.<AWS_REGION>.amazonaws.com/k8s/kube-bench:latest

4. Copy the URI of your pushed image, the URI format is like this: <AWS_ACCT_NUMBER>.dkr.ecr.<AWS_REGION>.amazonaws.com/k8s/kube-bench:latest
5. Replace the image value in job-eks-stig.yaml with the URI from Step 4
6. Run the kube-bench job on a Pod in your Cluster: kubectl apply -f job-eks-stig.yaml
7. Find the Pod that was created, it should be in the default namespace: kubectl get pods --all-namespaces
8. Retrieve the value of this Pod and output the report, note the Pod name will vary: kubectl logs kube-bench-<value>

• You can save the report for later reference: kubectl logs kube-bench-<value> > kube-bench-report.txt

Running on OpenShift

OpenShift Hardening Guide	kube-bench config
ocp-3.10 +	rh-0.7
ocp-4.1 +	rh-1.0

kube-bench includes a set of test files for Red Hat's OpenShift hardening guide for OCP 3.10 and 4.1. To run this you will need to specify --benchmark rh-07, or --version ocp-3.10 or,--version ocp-4.5 or --benchmark rh-1.0

kube-bench supports auto-detection, when you run the kube-bench command it will autodetect if running in openshift environment.

Since running kube-bench requires elevated privileges, the privileged SecurityContextConstraint needs to be applied to the ServiceAccount used for the Job:

oc create namespace kube-bench
oc adm policy add-scc-to-user privileged --serviceaccount default
oc apply -f job.yaml

Running in a GKE cluster

CIS Benchmark	Targets
gke-1.0	master, controlplane, node, etcd, policies, managedservices
gke-1.2.0	master, controlplane, node, policies, managedservices

kube-bench includes benchmarks for GKE. To run this you will need to specify --benchmark gke-1.0 or --benchmark gke-1.2.0 when you run the kube-bench command.

To run the benchmark as a job in your GKE cluster apply the included job-gke.yaml.

kubectl apply -f job-gke.yaml

Running in a ACK cluster

CIS Benchmark	Targets
ack-1.0	master, controlplane, node, etcd, policies, managedservices

kube-bench includes benchmarks for Alibaba Cloud Container Service For Kubernetes (ACK). To run this you will need to specify --benchmark ack-1.0 when you run the kube-bench command.

To run the benchmark as a job in your ACK cluster apply the included job-ack.yaml.

kubectl apply -f job-ack.yaml

Running in a VMware TKGI cluster

CIS Benchmark	Targets
tkgi-1.2.53	master, etcd, controlplane, node, policies

kube-bench includes benchmarks for VMware tkgi platform. To run this you will need to specify --benchmark tkgi-1.2.53 when you run the kube-bench command.

To run the benchmark as a job in your VMware tkgi cluster apply the included job-tkgi.yaml.

kubectl apply -f job-tkgi.yaml

Running in a Rancher RKE cluster

CIS Benchmark	Targets
rke-cis-1.7	master, etcd, controlplane, node, policies

kube-bench includes benchmarks for Rancher RKE platform. To run this you will need to specify --benchmark rke-cis-1.7 when you run the kube-bench command.

Running in a Rancher RKE2 cluster

CIS Benchmark	Targets
rke2-cis-1.7	master, etcd, controlplane, node, policies

kube-bench includes benchmarks for Rancher RKE2 platform. To run this you will need to specify --benchmark rke2-cis-1.7 when you run the kube-bench command.

Running in a Rancher K3s cluster

CIS Benchmark	Targets
k3s-cis-1.7	master, etcd, controlplane, node, policies

kube-bench includes benchmarks for Rancher K3S platform. To run this you will need to specify --benchmark k3s-cis-1.7 when you run the kube-bench command.